Systems and methods for remote monitoring of non-critically ill hospitalized patients

ABSTRACT

Described herein is a system for remote monitoring of non-critically ill hospitalized patients. The system can include a graphical user interface displaying a representation of the patient census. Each patient is represented by a graphic showing a clinical status, with an underlying expanded view of various parameters. The system can also include a non-transitory memory storing computer executable instructions and a processor configured to execute the computer executable instructions. Upon execution, the computer executable instructions can at least: receive a data stream associated with a non-critically ill hospitalized patient; determine a risk score associated with the non-critically ill hospitalized patient based on data associated with the alarm notification, wherein the risk score represents a probability of the non-critically ill hospitalized patient developing an actionable clinical event; and rearrange the plurality of graphical representations on the GUI based on the risk score.

RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional Application No.62/296,121, entitled “SYSTEMS AND METHODS FOR REMOTE MONITORING OFNON-ICU PATIENTS,” filed Feb. 17, 2016. The entirety of this provisionalapplication is hereby incorporated by reference for all purposes.

TECHNICAL FIELD

The present disclosure relates generally to remote monitoring ofnon-critically ill hospitalized patients and, more specifically, tosystems and methods that employ a vendor-agnostic, risk stratifiedpatient census with dynamic alerts to facilitate the remote monitoringof the non-critically ill hospitalized patients.

BACKGROUND

Traditionally, the responsibility for monitoring non-critically illpatients has fallen to bedside personnel. However, normal hospitalactivities occurring at a nursing station may distract the bedsidepersonnel from continuous, vigilant patient monitoring. For example,busy bedside personnel may suffer from “alarm fatigue”, becomingdesensitized to the constant noise of various non-actionable alarms.This fatigue may result in actionable alarms requiring clinicalintervention being missed.

Remote monitoring units can be a valuable tool for continuous monitoringof the physiologic condition of patients. Traditionally, these remotemonitoring units employ monitoring technicians, each viewing data for aplurality of patients using monitors from a common vendor. However,these remote monitoring units also suffer from alarm fatigue, in whichmultiple alarms are generated simultaneously without distinction oftheir associated clinical relevance. The large number of non-actionablealarms can overwhelm the monitoring technicians, causing the monitoringtechnicians to miss an actionable alarm requiring clinical intervention.Additionally, these traditional remote monitoring units are generallyunable to combine monitoring devices from different vendors efficientlyor mix patients being monitored by equipment on separate networks.

SUMMARY

The present disclosure relates generally to monitoring non-criticallyill hospitalized patients from a remote location, and, morespecifically, to systems and methods that employ a vendor-agnostic, riskstratified patient census with dynamic alerts to combat the problem ofalarm fatigue. The dynamic alerts can include the rearrangement ofpatients displayed on a graphical user interface (GU) according tocalculated risk scores for the particular patients.

In one aspect, the present disclosure includes a system that can monitornon-critically ill patients from a remote location. The system caninclude a graphical user interface displaying a plurality of graphicalrepresentations, each displaying a clinical status corresponding to aunique non-critically ill hospitalized patient. Each graphicalrepresentation is expandable to a detailed view comprising parameterscorresponding to the clinical status. The system can also include anon-transitory memory storing computer executable instructions; and aprocessor coupled to the memory and configured to execute the computerexecutable instructions. Upon execution the computer executableinstructions can at least: receive a data stream associated with anon-critically ill hospitalized patient; determine a risk scoreassociated with the non-critically ill hospitalized patient based ondata associated with the alarm notification, wherein the risk scorerepresents a probability of the non-critically ill hospitalized patientdeveloping an actionable clinical event; and rearrange the plurality ofgraphical representations on the GUI based on the risk score, The riskscore is related to the clinical status of the non-critically illhospitalized patient. In some instances, the data stream can be relatedto an alarm and the risk score can indicate whether the alarm isactionable or non-actionable.

In another aspect, the present disclosure includes a method formonitoring non-critically ill hospitalized patients from a remotelocation. The method can include displaying, on a graphical userinterface device by a system comprising a processor, a plurality ofgraphical representations, each graphical representation correspondingto a clinical status of a unique non-critically ill hospitalizedpatient; receiving, by the system, a data stream related to anon-critically ill hospitalized patient; determining, by the system, arisk score for the non-critically ill hospitalized patient based on dataderived from the data stream, wherein the risk score represents aprobability of the non-critically ill hospitalized patient developing anactionable clinical event; and rearranging, by the system, the displayof the plurality of graphical representations on the graphical userinterface based on the risk score for the non-critically illhospitalized patient. The risk score can be applied to the associatedexpanded view for the patient and synchronized to the electronic medicalrecord.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other features of the present disclosure will becomeapparent to those skilled in the art to which the present disclosurerelates upon reading the following description with reference to theaccompanying drawings, in which:

FIG. 1 is a block diagram showing a team approach for the remotemonitoring of non-critically ill hospitalized patients from a pluralityof different hospitals;

FIG. 2 is a block diagram showing types of information transfer withinone of the plurality of different hospitals for one non-critically illhospitalized patient;

FIG. 3 is a schematic diagram showing an example risk stratified patientdisplay in which the non-critically ill hospitalized patient with thehighest risk score rises to the top of the screen;

FIG. 4 is a block diagram showing a system that can monitornon-critically ill hospitalized patients from a remote location,according to an aspect of the present disclosure;

FIG. 5 is a schematic diagram showing the example risk stratifiedpatient display shown in FIG. 3 after another patient is determined toexhibit a higher risk score;

FIG. 6 is a process flow diagram illustrating a method for monitoringnon-critically ill hospitalized patients from a remote location, inaccordance with another aspect of the present disclosure; and

FIG. 7 is a process flow diagram illustrating a method for determining arisk score for a certain non-critically ill hospitalized patient thatcan be used in the method of FIG. 6 .

DETAILED DESCRIPTION I. Definitions

In the context of the present disclosure, the singular forms “a,” “an”and “the” can also include the plural forms, unless the context clearlyindicates otherwise.

The terms “comprises” and/or “comprising,” as used herein, can specifythe presence of stated features, steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, steps, operations, elements, components, and/or groups.

As used herein, the term “and/or” can include any and all combinationsof one or more of the associated listed items.

Additionally, although the terms “first,” “second,” etc. may be usedherein to describe various elements, these elements should not belimited by these terms. These terms are only used to distinguish oneelement from another. Thus, a “first” element discussed below could alsobe termed a “second” element without departing from the teachings of thepresent disclosure. The sequence of operations (or acts/steps) is notlimited to the order presented in the claims or figures unlessspecifically indicated otherwise.

As used herein, the term “remote monitoring” can refer to theobservation of a disease, condition, or one or more medical parametersover time at a location remote from the patient location. For example,remote monitoring can utilize telecommunication and informationtechnologies to provide telemetry services of remotely monitoring vitalsigns of non-critically ill hospitalized patients.

As used herein, a “remote” location can refer to any location in whichmedical practitioners therein are not delivering bedside patient care.One example of a remote location can include an off-site location fromthe premises of care delivery, such as an off-site central monitoringlocation. As another example, the remote location can be a sequesteredalcove adjacent to the premises of care delivery. Thus, the term“remote” is in relation to the fixed reference of bedside patient caredelivery and is independent from actual distance.

As used herein, the term “hospitalized patient” can refer to any patientreceiving medical care as an inpatient or under observation as anoutpatient.

As used herein, a hospitalized patient described as “non-critically ill”can refer to any hospitalized patient who is not critically ill in anintensive care unit (ICU). As an example, a non-critically illhospitalized patient can be a hospitalized patient who has beentransferred from the intensive care unit into a step-down unit. Asanother example, a non-critically ill hospitalized patient can be ahospitalized patient admitted to a general hospital unit that is not anintensive care unit. In another example, the non-critically illhospitalized patient can be an outpatient recovering from a surgicalprocedure, but released from the post-anesthesia care unit. As such, theterms “non-critical ill” hospitalized patient and “non-ICU” hospitalizedpatient can be used interchangeably.

As used herein, the term “vital signs” can refer to a group of one ormore medical characteristics that can be represented within one or moredata streams. The data streams can, either individually or together,indicate a status of a patient's life-sustaining functions.

The “data streams” can refer to any means of carrying medical datarelevant to the non-critically ill hospitalized patient to the remotemonitoring location. For example, the vital signs can be reflected inone or more data streams pertaining to temperature, heart rate,respiratory rate, systolic blood pressure, diastolic blood pressure,heart rhythm, pulse oximetry, oxygen saturation, intracranial pressure,or the like. In another example, the data streams can pertain to patientmotion, including acceleration, directionality, velocity or lackthereof, or the like. As a further example, the data streams can pertainto hemodynamic data, including central venous pressure, pulmonaryarterial systolic, diastolic or mean arterial pressure, pulmonarycapillary wedge pressure, left atrial pressure, left ventricular enddiastolic pressure, left ventricular end diastolic volume, cardiacoutput as measured in liters per minute, or cardiac index as measured inliters per minute over body surface area, or the like. In anotherexample, the data can be related to current or historical patientinformation derived from the electronic medical record, includingcurrent or prior medical conditions, family history including clinicallyrelevant chromosomal abnormalities, or genetic polymorphisms,pharmacotherapy, current or prior surgery or non-surgical invasivemedical procedures, or the like.

As used herein, the term “risk stratification” can refer to a process ofmedical decision making in which high risk or potentially high risknon-critically ill hospitalized patients are identified and theirmanagement prioritized. The risk stratification can be accomplished by a“risk score” representing a probability of a particular non-criticallyill hospitalized patient determined based on data derived from one ormore data streams.

As used herein, the term “patient census” can refer to the total numberof non-critically ill hospitalized patients being monitored by a remotemonitoring team.

As used herein, the term “remote monitoring team” can refer to a groupof monitoring technicians, each working individually or a group workingcollaboratively as a team.

As used herein, the term “clinical status” can refer to a state orcondition of a non-critically ill hospitalized patient. The clinicalstatus can be represented by one or more vital signs or any other datastream parameters (e.g., related to motion sensor data).

As used herein, the term “acuity” can refer to the level of severity ofan illness. For example, the non-critically ill hospitalized patientexhibiting the highest acuity characteristics can be prioritized.

As used herein, the term “vendor” can refer to a supplier of devicesused for monitoring non-critically ill hospitalized patients. Examplesof different vendors can include Philips, Siemens, General Electric, andthe like.

As used herein, the term “patient” can refer to any warm-bloodedorganism (e.g., a person) receiving treatment for a medical condition asan inpatient. In some instances, the patient may be a non-critically illhospitalized patient. For example, a non-critically ill patient can beany patient that is not being treated in a critical care unit like theintensive care unit (ICU).

As used herein, the term “hospital” can refer to any healthcare facilityin which a non-critically ill hospitalized patient is receiving medicalcare as an inpatient or under observation status. The terms “carecenter” and “hospital” can be used interchangeably herein.

As used herein, the term “electronic medical record” (EMR) can refer toa digital version of a patient's medical chart. In some instances, theelectronic medical record can be related to a particular patientencounter, which can be part of a larger electronic health record.

As used herein, the term “bedside team” can refer to one or moreclinical providers associated with a particular patient. The bedsideteam can include practitioners, nurses, an emergency response team, andthe like. The bedside team can include a wide range of personnelassociated with the patient at the hospital, including patient carenursing assistants (PCNAs), nursing, physicians, respiratory therapists,physician assistants (PAs), certified nurse practitioners (CNPs), andthe like.

II. Overview

The present disclosure relates generally to monitoring non-criticallyill hospitalized patients from a remote location. For example, thesenon-critically ill patients still require hospital care, but not thecritical care provided by an intensive care unit. More specifically, thepresent disclosure relates to systems and methods that employ avendor-agnostic, risk stratified patient census with dynamic alerts tofacilitate the remote monitoring of the non-critically ill hospitalizedpatients. Notably, the risk stratification can combat the problem ofalarm fatigue, ensuring that the highest acuity patient alarms areprioritized to be handled preferentially, either by action (e.g.,notifying appropriately-designed clinical personnel) or nullification.Additionally, the systems and methods can provide for streamlinedpaperless documentation of the encounter into the patient's electronicmedical record.

The remote monitoring described herein represents a significantdeparture from traditional monitoring by either bedside personnel orremote monitoring technicians viewing data for a plurality of patientsusing monitors from a common vendor. With the patient plurality assignedto each vendor, discordance in the total census, or acuity of patientsmonitored, is common and the inability to re-distribute patients amongvendors in an effort to balance the demands on monitoring personnelrepresents both a major problem and limitation. Traditional monitoringpersonnel and technicians can become overwhelmed by multiplesimultaneous patient alarms without distinction of the clinicalrelevance of each alarm. Moreover, traditional monitoring personnel andtechnicians have a limited capacity for nullification of non-actionablealarms. The remote monitoring, as described herein, distributes thecollective responsibility for monitoring a cohort of patients among ateam, allows mixing and combination of patients using an aggregated datastream from different networks and vendors, provides a mechanism bywhich the highest acuity patient alarms are prioritized (or rearrangedto a position of priority) on a display, provides a nullificationmechanism for non-actionable alarms; and provides for a data exchangewith the electronic medical record (EMR). Communication with bedsideclinical providers is enabled through an electronic medical record dataretrieval indicating name and contact information of providers, orthrough an electronic interface with a third party communication deviceprovider.

III. Systems

One aspect of the present disclosure relates to remote monitoring ofnon-critically ill hospitalized patients, in which the positions of thevarious patients can be rearranged on a GUI 17 according to a calculatedrisk score for each of the patients. FIG. 1 illustrates a team approach(e.g., a team can include monitoring personnel or technicians T1-TM,where M is an integer greater than or equal to 2) for the remotemonitoring of non-critically ill hospitalized patients from a pluralityof different hospitals (e.g., hospital 1-hospital N, where N is aninteger greater than or equal to 2) at a remote monitoring center 12with one or more graphical user interfaces (GUI 17). Notably, the remotemonitoring center 12 can accommodate hospitals 1-N 13-16 using differentnetworks and monitoring equipment from different vendors.

FIG. 2 shows an example of the care team for a single non-critically illhospitalized patient 22 at hospital 1 13. The care team can include abedside team of hospital-based personnel and the monitoring team at theremote monitoring center 12. The bedside team can include a practitioner23 (e.g., the admitting physician or licensed independent practitioner),the ward's nursing staff 24 (and other affiliated staff), and anemergency response team (e.g., an on call code team) 25 (and anyadditional hospital-based personnel). The nursing staff 24, theemergency response team 25, and the practitioner 23 responsible for thenon-critically ill hospitalized patient can change throughout the day(e.g., with each changing shift, the coverage for the specificnon-critically ill hospitalized patient can change). Similar bedsideteams exist for other non-critically ill hospitalized patients, both atthe same hospital or at different hospitals, but need not have the exactmembers illustrated in FIG. 2 .

Communication can occur between the remote monitoring center 12 and eachrespective hospital 13-16. In some instances, the communication can beuni-directional. For example, data 26 related to a non-critically illhospitalized patient 22 can be sent from hospital 1 13 to the remotemonitoring center 12 as one or more data streams. In other instances,the communication can be bi-directional. As an example, data 26 relatedto a non-critically ill hospitalized patient 22 can be sent fromhospital 1 13 to the remote monitoring center 12 as one or more datastreams and the remote monitoring center 12 can send one or morenotifications related to the non-critically ill hospitalized patient 22to hospital 1 13 (e.g., to the bedside team, an entity related to thehospital, to the patient's EMR, or the like). In some instances, thecommunication can take place in connection with the GUI 17.

Using the example shown in FIG. 2 , the remote monitoring center 12 canreceive one or more data streams including data 26 associated with thenon-critically ill hospitalized patient 22 from hospital 1 13. The datastreams can be related to data 26 from monitoring equipment, EMRs, notesfrom the bedside team, or the like. For example, data streams from themonitoring equipment can include data related to one or more monitoredvital signs. These data streams can be from different monitoringequipment using different protocols (e.g., from different vendors). Asanother example, the data streams from the monitoring equipment caninclude at least one alarm. The data streams can also include notes fromthe practitioner 23, the nursing staff 24, and/or the emergency responseteam 25. As another example, the data streams can come from or beassociated with the non-critically ill hospitalized patient's EMR.

The remote monitoring center 12 can receive the one or more data streamsand determine a risk score associated with the single non-critically illhospitalized patient 22. For example, the risk score can indicate aclinical status or a change in a clinical status of the non-criticallyill hospitalized patient. A patient census that includes patients beingmonitored by the remote monitoring center 12 can be displayed on one ormore graphical user interfaces 17. In some instances, the patient censuscan include all of the patients being monitored by the remote monitoringcenter 12. In other instances, the remote monitoring center 12 candisplay a portion of the patients being monitored by the remotemonitoring center 12 (e.g., each remote monitoring team can view apatient census that includes only the patients the team is monitoring).In still other instances, the patient census can include a masterpatient census with all of the patients being monitored by the remotemonitoring center 12 and a focused (zoomed in) patient census focusingon a subset of the entire patient census.

An example of a patient census being displayed on a GUI 17 is shown inFIG. 3 . The patient census can include a plurality of patients beingmonitored at a plurality of different hospitals, including:

Hospital 1

-   -   K. Patient    -   C. Patient

Hospital 2

-   -   Z. Patient    -   J. Patient

Hospital 3

-   -   A. Patient    -   G. Patient

Hospital N

-   -   F. Patient        Each of the patients can be represented graphically (e.g., by an        icon, a tile, or other graphical representation) on the GUI 17.

Each of the patients can be associated with a risk score (high, medium,low, as illustrated in FIG. 3 ). For example, the risk score can berelated to a risk of the patient developing an actionable clinicalevent. This risk score can be calculated for each patient and thedisplay configured based on the calculated risk scores.

Based on the calculated risk scores, the display shown in FIG. 3 can berisk stratified, such that the highest acuity patient is displayed mostprominently. For example, C. Patient at Hospital 1, can have the highestdetermined risk score (e.g., “high”) indicating the highest acuity andthe highest likelihood of developing an actionable clinical event.Accordingly, C. Patient can be displayed the most prominently on the GUI17. For example, C. Patient can be displayed in a different color, bedisplayed with an animation (e.g., blinking, shaking, or the like), bedisplayed zoomed in compared to the other patients, or the like.Patients with a “medium” risk score can have an elevated likelihood ofdeveloping an actionable clinical event—e.g., A. Patient at Hospital 3and Z. Patient at Hospital 2. Patients with a “low” risk score can havesmall likelihood of developing an actionable clinical event, including:K. Patient at Hospital 1, F. Patient at Hospital N, J. Patient atHospital 2, and G. Patient at Hospital 3. One way to distinguish thesepatients is color, with the high risk being red, the medium risk beingyellow, and the low risk being green. However, the different risk levelscan be distinguished in other ways (e.g., size, oscillatory movement,blinking, etc.). Moreover, the high, medium, and low risk scores can berelative to each other. For example, the highest risk score simplycorresponds to the patient requiring the most immediate attention. Inother instances, the high, medium, and low risk scores can be relativeto one or more thresholds set by the remote monitoring center 12 (e.g.,a patient with an alarm can be a high risk score, a patient with one ormore vital sign potentially trending in the wrong direction could be amedium risk score, and a patient with normal vital signs and no alarmscan be a low risk score). In some instances, the one or more thresholdscan be set by an algorithm associated with the remote monitoring center12. In other instances, the one of more thresholds can be set by thejudgment of one or more technicians at the remote monitoring center 12.In still other instances, the one or more thresholds can be setaccording to a policy set for the remote monitoring center 12.

One or more technicians at the remote monitoring center 12 can selectany one of the patients on the display and an expanded view of thepatient will be displayed. For example, the highest acuity patient (likeC. Patient at Hospital 1) can be selected, as illustrated in FIG. 3 .The expanded view can include detailed information for the individualnon-critically ill hospitalized patient (in some instances, structuredbased on the risk score). The detailed information, in some instances,can be set up to facilitate the discrimination of an actionable alarmand a non-actionable alarm. In some instances, the detailed view caninclude patient information, which can indicate one or more members ofthe bedside care team as responsible for the non-critically illhospitalized patient. For example, with different shifts, differentnurses and other staff members may be associated with the non-criticallyill hospitalized patients. Technician(s) at the remote monitoring center12 can alert the one or more members of the bedside care team of therisk score and/or any actionable alarm for the non-critical hospitalizedpatient (e.g., C. Patient). The patient information can also includeinformation, such as room number, ward, physician, diagnosis, age, timemonitored, and the like. In this example, the expanded view can alsoinclude information about one or more vital signs (at least a portion ofwhich can be associated with the alarm), information about the alarm,and a timer (e.g., a quality assurance stopwatch timer), which can beused to gauge the time it take the remote monitoring center 12 todetermine whether the alarm is actionable or non-actionable. Forexample, the timer can track the time since the patient was last viewedby a monitoring technician, track the time it takes the monitoringtechnician to view the alarm and eventually nullify the alarm, and thelike, for data reporting and quality assurance purposes. Additionally,in some instances, at least a portion of the additional information canbe displayed on the initial display with the patient icon or tile.

The GUI 17 display is altered by selection of the patient icon or tilewith an expanded display for the individual patient inclusive of thefollowing: 1) reason for the priority score-driven change in clinicalstatus, 2) ECG waveform, 3) bedside monitoring vendor alarms history, 4)trended vitals data. A stopwatch timer commences from the closure of thepatient tile after an expanded review to record the time since the tilewas last selected. In some instances, results of the stopwatch timer canbe reported to the EMR, the hospital, or any other agency monitoring theresponsiveness of the remote monitoring center 12 and/or trackingclinical and quality outcomes.

As an example, the risk score can be calculated based on a sum of threeindividual components—a monitoring indication risk score derived basedon a clinical event rate for a given monitoring indication, a vitalstrending risk score based on at least two vital signs, and an alarmsinput risk score based on the clinical relevance of an alarm. A system40 (FIG. 4 ) can include components that can be embodied on one or morecomputing devices that include a non-transitory memory 42 to storeinstructions and a processor 43 to facilitate execution of theinstructions. In some instances, a receiver 44, a scorer 45 and/or anupdater 47 can be stored as computer program instructions in thenon-transitory memory 42 and executed by the processor 43. The processor43 can be any type of device (e.g., a central processing unit, amicroprocessor, or the like) that can facilitate the execution of thecomputer program instructions to determine the risk score. Thenon-transitory memory 42 can include one or more non-transitory medium(not a transitory signal) that can contain or store the programinstructions for use by or in connection with matching patients withclinical trials by matching patient data to eligibility criteria.Examples (a non-exhaustive list) of non-transitory media can include: anelectronic, magnetic, optical, electromagnetic, infrared, orsemiconductor system, apparatus or device. More specific examples (anon-exhaustive list) of non-transitory media can include the following:a portable computer diskette; a random access memory; a read-onlymemory; an erasable programmable read-only memory (or Flash memory); anda portable compact disc read-only memory.

In this example, the system 40 can determine the risk score based on aninput data stream 41 received by a receiver 44. It will be understoodthat the receiver 44 can receive data streams related to physiologicchanges in each of the plurality of patients. The data stream 41 can beformatted according to a standard for transmission of clinical data,such as Health Level-7 (HL-7) or the like. The receiver 44 can be vendoragnostic, so the data stream 41 can be from any one of a number ofvendors of monitoring equipment. The receiver 44 can mine the data(e.g., including at least two vital signs and an alarm) from the datastream 41 and send the data to the scorer 45 for calculation of the riskscore 46, which can be used in the risk stratification of the GUI 17.

For example, the risk score 46 can be determined by the scorer 45 bysumming a monitoring indication risk score (MIRS), a vitals trendingrisk score (VTRS), and an alarms input risk score (AIRS) (in otherwords, Risk Score=MIRS+VTRS+AIRS). The MIRS can be derived from anemergency response team (ERT) (e.g., emergency response team 25) eventrate for a given monitoring indication (Xn=% ERT event rate for n/1.5)(e.g., syncope ERT event rate 4%; heart failure, acute ERT event rate2%). The VTRS can be determined based on at least two vital signs fromthe data stream 41. The VTRS can be based on trends associated with theat least two vital signs (e.g., at least two of a systolic bloodpressure, a diastolic blood pressure, a heart rate, a heart rhythm, apulse oximetry, a respiratory rate, an oxygen saturation, and anintracranial pressure). The trends can be determined by comparing acurrent vital sign (Yc) to a moving average (Yma) of the vital sign overthe last certain number of hours (e.g., 2 hours, 4 hours, 6 hours,etc.). For example, the moving average can be based on data stored inthe non-transitory memory 42. The trends can be calculated for each keymonitored vital sign. Any unmeasured parameter can drop out of theequation and carries no value. For example, VTRS can be calculated as asum of the weighted difference between the current vital sign and themoving average of the vital sign scaled by a weighted monitoringconstant specific to the vital sign. The AIRS can be determined based ona value assigned to the alarm triggered on the monitoring system (Zr).The value can be, for example, a numeric value (e.g., ranging from50-200) based on a priority of the specific alarm. The priority can bederived based on a table that lists each alarm by vendor with a derivedassigned value weighted based upon historical clinical outcomes data.For example, the assigned value can be derived based on historical datacollected over time related to the alarms (e.g., the historical data canbe stored in the non-transitory memory 42).

The risk score can represent a probability of the particular patientdeveloping an actionable clinical event. The updated risk score can besent to the updater 47 to change the graphical representation of theclinical status of the plurality of patients (e.g., shown in FIG. 5 )based on the determined risk score. As shown in FIG. 5 , the risk scorefor Z. Patient at Hospital 2 has changed from yellow to red, indicatingthat Z. Patient at Hospital 2 now has a higher priority than C. Patientat Hospital 1. As shown in FIG. 5 , the display of the patient censuscan be rearranged when a risk score for a patient increases, indicatinga higher acuity for that particular patient. The higher acuity can berealized according to a dynamic alert that can be visualized on the GUI17 by a change in the displayed clinical status. For example, the GUI 17can be automatically refreshed and rearranged according to continuousupdates by one or more real-time patient data streams.

The GUI 17 seen by the remote monitoring center 12, in some instances,can allow one or more technicians (T1-TM 18) at the remote monitoringcenter 12 interaction with updater 47. For example, the GUI 17 canprovide one or more of the technicians with the ability to assess analert and nullify the alert if deemed non-actionable. This interactionby the technicians with the GUI 17 is also available afteridentification and communication of an actionable clinical event.Communication with bedside clinical providers is enabled throughelectronic medical record data retrieval indicating name and contactinformation of providers, or through an electronic interface with athird party communication device provider. Once this communication hasoccurred, the technicians record an interaction with the updater 47which nullifies this actionable clinical event's high risk graphicalrepresentation for a predetermined period of time (e.g. two to thirtyminutes).

IV. Methods

Another aspect of the present disclosure can include a method 60 formonitoring patients from a remote location (FIG. 6 ). In some instances,the patients can be non-critical hospitalized patients from a pluralityof different hospitals. The different hospitals can use monitoringdevices from different vendors. The method 60 can be vendor agnostic,allowing inputs from each of the different monitoring devices from thedifferent vendors. The monitoring of method 60 can provide a riskstratified patient census with dynamic alerts (e.g., as shown in thetransition between FIG. 3 and FIG. 5 ) to enable the monitoring of theplurality of non-ICU patients. FIG. 7 shows an example of a method 70for determining a risk score for a certain patient that can be used inthe risk stratification of the method 60 shown in FIG. 6 .

The methods 60 and 70 are illustrated as process flow diagrams withflowchart illustrations, which can be implemented by one or morecomponents of the system 40, as shown in FIG. 4 . For purposes ofsimplicity, the methods 60 and 70 are shown and described as beingexecuted serially; however, it is to be understood and appreciated thatthe present disclosure is not limited by the illustrated order as somesteps could occur in different orders and/or concurrently with othersteps shown and described herein. Moreover, not all illustrated aspectsmay be required to implement the methods 60 and 70.

One or more blocks of the respective flowchart illustrations, andcombinations of blocks in the block flowchart illustrations, can beimplemented by computer program instructions. These computer programinstructions can be stored in memory and provided to a processor of ageneral purpose computer, special purpose computer, and/or otherprogrammable data processing apparatus to produce a machine, such thatthe instructions, which execute via the processor of the computer and/orother programmable data processing apparatus, create mechanisms forimplementing the steps/acts specified in the flowchart blocks and/or theassociated description. In other words, the steps/acts can beimplemented by a system comprising a processor that can access thecomputer-executable instructions that are stored in a non-transitorymemory.

The methods 60 and 70 of the present disclosure may be embodied inhardware and/or in software (including firmware, resident software,micro-code, etc.). Furthermore, aspects of the present disclosure maytake the form of a computer program product on a computer-usable orcomputer-readable storage medium having computer-usable orcomputer-readable program code embodied in the medium for use by or inconnection with an instruction execution system. A computer-usable orcomputer-readable medium may be any non-transitory medium that cancontain or store the program for use by or in connection with theinstruction or execution of a system, apparatus, or device.

Referring now to FIG. 6 , illustrated is a method 60 for monitoringnon-critically ill hospitalized patients from a remote monitoring center(e.g., remote monitoring center 12) at a remote location. At 61, agraphical representation of a clinical status of a plurality ofnon-critically ill hospitalized patients (e.g., each of the plurality ofnon-critically ill hospitalized patients represented by tiles or icons,as shown in FIG. 3 , with a clinical status for each of the plurality ofnon-critically ill hospitalized patients displayed in an easilyperceivable way, such as in a certain color or oscillatory motion) canbe displayed (e.g., at remote monitoring center 12). The graphicalrepresentation can be displayed on a graphical user interface (e.g., GUI17) that can be viewed by a plurality of monitoring technicians (e.g.,T1-TM 18) assigned to the plurality of non-critically ill hospitalizedpatients.

The remote monitoring center 12 can be linked to a plurality ofhospitals (e.g., hospital 1-hospital N 13-16), which can potentially usemonitoring devices from different vendors. At 62, a data stream (e.g.,data stream 41) can be received (e.g., by receiver 44) from one of thehospitals related to at least one of the plurality of non-critically illhospitalized patients. It will be understood that the remote monitoringcenter 12 can receive a plurality of data streams corresponding todifferent non-critically ill hospitalized patients from the differenthospitals generated by machines from different vendors. The data streamscan be formatted in accordance with a standard for transfer of clinicaldata, such as Health Level-7 (HL-7) or other data transmission standard.The receiver can process the data stream to retrieve or derive medicaldata (e.g., including at least two vital signs associated with the atleast one non-critically ill hospitalized patient and an alarm triggeredby a monitoring device associated with the at least one non-criticallyill hospitalized patient). The medical data can be sent to a scorer(e.g., scorer 45), which, as 63, can determine a risk score for the atleast one of the plurality of non-critically ill hospitalized patientsbased on the medical data. The risk score can represent a probability ofthe at least one of the plurality of non-critically ill hospitalizedpatients developing an actionable clinical event. The updated risk scorecan be sent to an updater (e.g., updater 47), which can, at 64, changethe graphical representation of the clinical status of the plurality ofnon-critically ill hospitalized patients (e.g., shown in FIG. 5 ) basedon the determined risk score.

For example, a second data stream, which can be from a different vendor,can be received. The second data stream can be related to another atleast one of the plurality of non-critically ill hospitalized patients.Another risk score can be determined for the another at least one of theplurality of non-critically ill hospitalized patients based on medicaldata derived from the another data stream. The graphical representationof the clinical status can be changed (e.g., issuing a dynamic alert) toillustrate the newly calculated another risk score. When the anotherrisk score illustrates that the another non-critically ill hospitalizedpatient has a risk score that is higher than any other of the pluralitynon-critically ill hospitalized patients, the GUI 17 can be dynamicallyupdated to illustrate the another of the plurality of non-critically illhospitalized patients in a more prominent position, indicating thehigher risk score.

FIG. 7 illustrates a method 70 for determining a risk score for acertain non-critically ill hospitalized patient that can be used in therisk stratification. For example, the risk score of FIG. 6 can bedetermined by the scorer (e.g., scorer 45) according to the method 70.At 71, a monitoring indication risk score (MIRS) can be determined. Forexample, the MIRS can be derived from an event rate for a givenmonitoring indication (Xn=% ERT event rate for n/1.5). At 72, a vitalstrending risk score (VTRS) can be determined based on at least two vitalsigns from the data stream. The VTRS can be based on trends associatedwith the at least two vital signs (e.g., at least two of a systolicblood pressure, a diastolic blood pressure, a heart rate, a heartrhythm, a pulse oximetry, a respiratory rate, an oxygen saturation, oran intracranial pressure). The trends can be determined by comparing acurrent vital sign (Yc) to a moving average (Yma) of the vital sign overthe last certain number of hours (e.g., 2 hours, 4 hours, 6 hours, 8hours, 12 hours, or the like). The trends can be calculated for each keymonitored vital sign. Any unmeasured parameter can drop out of theequation and carries no value. For example, VTRS can be calculated as asum of the weighted difference between the current vital sign and themoving average of the vital sign scaled by a weighted monitoringconstant specific to the vital sign (e.g., an integer value greater than2, in some instances from 5 to 300). At 73, an alarms input risk score(AIRS) can be determined. A value can be assigned to the alarm triggeredon the monitoring system (Zr). The value can be, for example, a numericvalue (e.g., ranging from 5-100) based on a priority of the specificalarm. The priority can be derived based on a table that lists eachalarm by vendor with a derived assigned value. For example, the assignedvalue can be derived based on historical data collected over timerelated to the alarms. At 74, the risk score can be determined bysumming the MIRS, the VTRS, and the AIRS (Risk Score=MIRS+VTRS+AIRS).

The risk score can be used according to the following example. A centralmonitoring station of the remote monitoring center can include agraphical user interface (e.g., GUI 17) that can display a patientcensus with an associated, readily-discernible clinical status for eachnon-critically ill hospitalized patient. The GUI corresponding to theplurality of non-critically ill hospitalized patients can be monitoredby a small group of technicians working together to provide team-basedmonitoring with notifications to bedside clinical providers. Detaileddata for the patient can be viewed by selecting the patient tile oricon. The GUI display is based on determined risks of each of thepatients developing an actionable clinical event. The risks can bequantified as a Priority Risk Score (or “risk score”), which iscalculated based on a sum of three individual components—a monitoringindication risk score, a vitals trending risk score based on at leasttwo vital signs, and an alarms input risk score based on the clinicalrelevance of an alarm. The display of the patient census can change whena risk score for a patient increases, indicating a higher acuity for thepatient. The higher acuity can be realized according to a dynamic alertthat can be visualized on the GUI by a change in the displayed clinicalstatus. The application of color and oscillatory motion to the patienttile or icon visually represents a change in clinical status on thedisplay. A stopwatch timer commences from the onset of change inclinical status until the tile is selected for expanded review by themonitoring technician. The timer variable can be used for qualityassurance purposes, or for tracking of clinical outcomes. The expandedview provides detailed information for the individual patient asstructured by the risk score to facilitate the discrimination of anactionable alarm and nullification of a non-actionable alarm.

V. Examples

The following Examples show the operation of the system shown in FIGS.1-5 in the case of a hypothetical high risk patient, low risk patient,and moderate risk patient.

High Risk Patient Scenario

A new patient (Patient H) is admitted to Hospital 1 13 with a high-riskindication for telemetry order in the associated electronic medicalrecord (EMR). The telemetry order is communicated to nursing 24 andmonitoring technicians 18 at a remote monitoring center 12. Thetelemetry order is also accessible to all practitioners 23 in additionto the emergency response team 25 at Hospital 1 13. A graphical userinterface (GUI) 17 at the remote monitoring center 12 associated withthe technicians is updated with a representation of Patient H (e.g., atile or icon view and an expanded view as described above).

Upon application of one or more monitoring devices to Patient H atHospital 1 13, the representation of Patient H on the GUI 17 is updatedto indicate, by color: a monitoring indication risk score 71, a vitalstrending risk score 72, and an alarms input risk score 73. For PatientH, this includes a high risk indication, stable vital signs, and nomonitoring alarms, leading to an initial risk score 74 of “low”. Therepresentation of Patient H on the GUI can be configured as “low risk”.However, Patient H can experience a significant change to the vitalsigns and multiple monitor alarms, which change the risk score 74 from“low” to “high”. The changes to the vital signs and the multiple monitoralarms are received via data streams 41 to the receiver 44. The receiver44 sends the data streams 41 to the scorer 45, which determines a riskscore 46 based on the combination of the telemetry indication(monitoring indication, the vital signs, and the monitor alarms). Thescorer 45 sends the risk score and the updated data to the updater 47,which updates the GUI 17 to reflect the “high risk” of Patient H (e.g.,a color change and/or oscillatory motion).

Due to the “high” risk score, Patient H rises to the top of the screenof the GUI 17. The change in the GUI 17 triggers a response from one ormore of the monitoring technicians 18. The response can be communicatingwith the bedside nursing personnel 24 and/or the emergency response team25 regarding the significant change. The bedside nursing personnel 24and/or the emergency response team 25 can interact with Patient H toprovide resuscitative or supportive measures, as needed. The monitoringtechnician interacts with the updater 47 through the GUI 17 to indicatea change in the status of this actionable alarm. The updater 47transmits this data to the scorer 45 to generate an updated risk score46, which can flow back through the updater 47 to reflect a temporarilylower score on the GUI 17 (e.g., medium or high, but lower acuity). Thetemporarily lower score is based on the communication notifying the careteam of Patient H′s change. If the care team cancel the alarm and/orcause a change in the vital signs, the risk score can return to “lowrisk” and the representation of Patient H on the GUI 17 can return tothe lower portion of the GUI 17.

Low-Risk Patient Scenario

Patient L is admitted to Hospital 2 14 with a low-risk indication fortelemetry order in the electronic medical record. The order iscommunicated via EMR to nursing 24 and monitoring technicians 18 atremote monitoring center 12. The telemetry order is also accessible toall practitioners 23 in addition to the emergency response team 25 atHospital 2. A graphical user interface (GUI) 17 at the remote monitoringcenter 12 associated with the technicians is updated with arepresentation of Patient L (e.g., an tile or icon view and an expandedview as described above).

Upon application of one or more monitoring devices to Patient L, therepresentation of Patient L on the GUI 17 is updated to indicate, bycolor: a monitoring indication risk score 71, a vitals trending riskscore 72, and an alarms input risk score 73. For Patient L, thisincludes a low risk indication, stable vital signs, and no monitoringalarms, leading to an initial risk score 74 of “low”. This GUI 17 isviewed by a team of monitoring technicians 18 at the remote monitoringcenter 12. This team is also monitoring patients from Hospital 1 13,Hospital 3 15, and Hospital N 16 on their risk stratified patientdisplay (shown, for example, in FIG. 3 ).

During Patient L's time on the monitoring system, there are nosignificant changes requiring intervention from the remote monitoringcenter 12. Upon discharge, this patient's monitoring equipment isremoved and information is discharged from the monitoring system, thusremoving the icon representing Patient L from the GUI 17 visible to theremote monitoring center 12. The patient's EMR can be updated withinformation regarding the discharge.

Moderate-Risk Patient Scenario

Patient M is admitted to Hospital 2 14 with a low risk indication fortelemetry order in the electronic medical record. The order iscommunicated via EMR to nursing 24 and monitoring technicians 18 at theremote monitoring center 12. The telemetry order is also accessible toall practitioners 23 in addition to the emergency response team 25 atHospital 2. A graphical user interface (GUI) 17 at the remote monitoringcenter 12 associated with the technicians is updated with arepresentation of Patient M (e.g., a tile or icon view and an expandedview as described above).

Upon application of one or more monitoring devices, the representationof Patient M on the GUI 17 is updated to indicate, by color: amonitoring indication risk score 71, a vitals trending risk score 72,and an alarms input risk score 73. For Patient M, this includes a lowrisk indication, stable vital signs, and no monitoring alarms, leadingto an initial risk score 74 of “low”. However, Patient M can experiencea significant change to the vital signs and multiple monitor alarms,which change the risk score 74 from “low” to “moderate”. The changes tothe vital signs and the multiple monitor alarms are received via datastreams 41 to the receiver 44. The receiver 44 sends the data streams 41to the scorer 45, which determines a risk score 46 based on thecombination of the telemetry indication (monitoring indication), thevital signs, and the monitor alarms. The scorer 45 sends the risk scoreand the updated data to the updater 47, which updates the GUI 17 toreflect the “moderate risk” of Patient M (e.g., a color change and/oroscillatory motion).

During Patient M's time on the monitoring system, Patient M experiencesa change in vital signs resulting in Patient M's overall level of riskmoving from “low” to “moderate”. These changes are received via datastream 41 to the receiver 44. The receiver 44 sends this data stream 41to the scorer 45, which determines a risk score 46 based on thecombination of the telemetry indication, vital signs, and monitoralarms. The scorer 45 then sends the updated risk score and/or the datato the updater 47, which updates the GUI 17 to reflect a color changeand/or oscillatory motion of Patient M′s representation.

With a moderate level of overall risk, Patient M rises to the middle ofthe screen. The GUI 17 change triggers a response from the monitoringtechnicians 18 at the remote monitoring center 12. For example, one ormore monitoring technicians will review the patient's now moderate riskscore 46 and associated vitals trending risk score 72 to determine ifthe moderate risk score is actionable. After review, changes aredetermined to be non-actionable and nullified in the updater 47 throughthe GUI 17, which indicates the change in the status of thisnon-actionable alarm. For example, the indication of the non-actionablealarm can be an indication taken by the monitoring technician, such asactively selecting an “alarm nullify” indication on the GUI 17. Thenullification can be updated to the EMR. The updater 47 transmits thisdata to the scorer 45 to generate an updated risk score 46, which flowsback through the updater 47 to reflect a temporary lower score on theGUI 17. This new score is based on the review by the monitoringtechnician. Once Patient M has a lower score the icon representingPatient M on the GUI 17 returns to the lower portion of the riskstratified patient display (shown in FIG. 3 ). Upon discharge, thispatient's monitoring equipment is removed and information is dischargedfrom the monitoring system, thus removing the representation on the GUI17 visible to the remote monitoring center 12.

From the above description, those skilled in the art will perceiveimprovements, changes and modifications. Such improvements, changes andmodifications are within the skill of one in the art and are intended tobe covered by the appended claims.

What is claimed is:
 1. A system comprising: a graphical user interfacein a remote monitoring center comprising a display of a plurality ofgraphical representations, each of the plurality of graphicalrepresentations displaying a clinical status corresponding to a uniquenon-critically ill hospitalized patient, wherein each of the pluralityof graphical representations is expandable to a detailed view comprisingparameters corresponding to the clinical status corresponding to theunique non-critically ill hospitalized patient, wherein the remotemonitoring center is at an offsite central monitoring center remote fromthe plurality of unique non-critically ill hospitalized patients; anon-transitory memory storing computer executable instructions; and aprocessor coupled to the memory and configured to execute the computerexecutable instructions to at least: receive a data stream associatedwith one of the plurality of non-critically ill hospitalized patients,wherein the data stream comprises at least two vital signs associatedwith the one of the plurality of non-critically ill hospitalizedpatients and an alarm notification associated with the one of theplurality of non-critically ill hospitalized patients; determine a riskscore associated with the one of the plurality of non-critically illhospitalized patients by summing at least a vitals trending risk scoredetermined based on values associated with the at least two vital signsa monitoring indication risk score, and an alarm input risk scoredetermined based on a value assigned to a triggered alarm based on apriority of the triggered alarm, wherein the priority of the triggeredalarm is based on a vendor and an assigned weighted value derived basedon historical clinical outcomes data of the triggered alarm, wherein therisk score indicates whether an alarm associated with the alarmnotification is actionable or not actionable based on a likelihood ofthe non-critically ill hospitalized patient developing an actionableclinical event; categorize the risk score associated with the one of theplurality of non-critically ill hospitalized patients as one of high,medium, or low, wherein the risk score is categorized by comparing therisk score to at least two thresholds set by the remote monitoringcenter; and rearrange the plurality of graphical representations on thedisplay when the risk score associated with the one of the plurality ofnon-critically ill hospitalized patients changes to undergo a visualchange and to move: graphical representations representing high riskscore non-critically ill hospitalized patients to display moreprominently than graphical representations representing medium and lowrisk score non-critically ill hospitalized patients, the graphicalrepresentations representing medium risk score graphical representationsto display less prominently than the graphical representationsrepresenting high risk score non-critically ill hospitalized patientsand more prominently than the low risk score graphical representations,and the graphical representations representing low risk score graphicalrepresentations to display less prominently than the graphicalrepresentations representing medium and high risk scores.
 2. The systemof claim 1, wherein the processor quantifies a responsiveness of themonitoring technician based on a time to view the detailed view of theparameters triggering the risk score.
 3. The system of claim 1, whereinthe detailed view comprises real-time ECG waveform data, stored alarmedECG data, bedside monitoring vendor alarms history, trended vitals data,and a communication link to a bedside clinical provider.
 4. The systemof claim 1, wherein each graphical representation is linked to anelectronic medical record (EMR) of the corresponding uniquenon-critically ill hospitalized patient to provide direct paperlessdocumentation of any change in clinical status and a correspondingindividual notified.
 5. The system of claim 1, wherein the monitoringindication risk score is derived based on a clinical event rate for agiven monitoring indication.
 6. The system of claim 1, wherein thevalues associated with the at least two vital signs are based on trendsassociated with the at least two vital signs.
 7. The system of claim 6,wherein the trends are determined based on summing scaled differencesbetween the at least two vital signs and moving averages of the at leasttwo vital signs over a time period scaled.
 8. The system of claim 7,wherein the scaled differences are scaled by a constant specific to eachof the at least two vital signs.
 9. The system of claim 1, wherein theat least two vital signs comprise at least two of a systolic bloodpressure, a diastolic blood pressure, a heart rate, a heart rhythm, apulse oximetry, a respiratory rate, an oxygen saturation, motion data,and an intracranial pressure.
 10. The system of claim 1, wherein thevisual change comprises a color change when the risk score associatedwith the one of the plurality of non-critically ill hospitalizedpatients is categorized differently.
 11. A method comprising:displaying, on a display of a graphical user interface device in aremote monitoring center by a system comprising a processor, a pluralityof graphical representations, each of the plurality of graphicalrepresentations corresponding to a clinical status of a uniquenon-critically ill hospitalized patient, wherein each of the pluralityof graphical representations is expandable to a detailed view comprisingparameters corresponding to the clinical status corresponding to theunique non-critically ill hospitalized patient, wherein the remotemonitoring center is at an offsite central monitoring center remote fromthe plurality of unique non-critically ill hospitalized patients;receiving, by the system, a data stream related to one of the pluralityof non-critically ill hospitalized patients, wherein the data streamcomprises at least two vital signs associated with the one of theplurality of non-critically ill hospitalized patients and an alarmnotification associated with the one of the plurality of non-criticallyill hospitalized patients; determining, by the system, a risk score forthe one of the plurality of non-critically ill hospitalized patients bysumming at least a vitals trending risk score determined based on valuesassociated with the at least two vital signs, a monitoring indicationrisk score based on an event rate for a given medical indication, and analarm input risk score determined based on a value assigned to atriggered alarm based on a priority of the triggered alarm, wherein thepriority of the triggered alarm is based on a vendor and an assignedweighted value derived based on historical clinical outcomes data of thetriggered alarm, wherein the risk score indicates whether an alarmassociated with the alarm notification is actionable or not actionablebased on a likelihood of the non-critically ill hospitalized patientdeveloping an actionable clinical event; categorizing, by the system,the risk score associated with the one of the plurality ofnon-critically ill hospitalized patients as one of high, medium, or low,wherein the risk score is categorized by comparing the risk score to atleast two thresholds set by the remote monitoring center; andrearranging, by the system, the display of the plurality of graphicalrepresentations on the graphical user interface when the risk scoreassociated with the one of the plurality of non-critically illhospitalized patients is categorized differently to undergo a visualchange and to move: graphical representations representing high riskscore non-critically ill hospitalized patients to display moreprominently than graphical representations representing medium and lowrisk score non-critically ill hospitalized patients, the graphicalrepresentations representing medium risk score graphical representationsto display less prominently than the graphical representationsrepresenting high risk score non-critically ill hospitalized patientsand more prominently than the low risk score graphical representations,and the graphical representations representing low risk score graphicalrepresentations to display less prominently than the graphicalrepresentations representing medium and high risk scores.
 12. The methodof claim 11, wherein the rearranged display triggers a monitoringtechnician to view a detailed view of parameters triggering the riskscore.
 13. The method of claim 11, further comprising quantifying aresponsiveness of the monitoring technician based on a time to view thedetailed view of the parameters triggering the risk score.
 14. Themethod of claim 11, further comprising: nullifying, by the system, thealarm based on the risk score; and rearranging, by the system, thedisplay of the plurality of graphical representations based on thenullified alarm.
 15. The method of claim 11, wherein the detailed viewcomprises real-time ECG waveform data, stored alarmed ECG data, bedsidemonitoring vendor alarms history, trended vitals data, a communicationlink to an assigned nurse, and emergency response team contacts.
 16. Themethod of claim 11, wherein each graphical representation is linked toan electronic medical record (EMR) of the corresponding non-criticallyill hospitalized patient to provide direct paperless documentation ofany change in clinical status and a corresponding individual notified.